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The variants of the Bees Algorithm (BA): a survey

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Abstract

The Bees Algorithm (BA) is a bee swarm intelligence-based metaheuristic algorithm that is inspired by the natural behavior of honeybees when foraging for food. BA can be divided into four parts: parameter tuning, initialization, local search, and global search. Since its invention, several studies have sought to enhance the performance of BA by improving some of its parts. Thus, more than one version of the algorithm has been proposed. However, upon searching for the basic version of BA in the literature, unclear and contradictory information can be found. By reviewing the literature and conducting some experiments on a set of standard benchmark functions, three main implementations of the algorithm that researchers should be aware of while working on improving the BA are uncovered. These implementations are Basic BA, Shrinking-based BA and Standard BA. Shrinking-based BA employs a shrinking procedure, and Standard BA uses a site abandonment approach in addition to the shrinking procedure. Thus, various implementations of the shrinking and site-abandonment procedures are explored and incorporated into BA to constitute different BA implementations. This paper proposes a framework of the main implementations of BA, including Basic BA and Standard BA, to give a clear picture of these implementations and the relationships among them. Additionally, the experiments show no significant differences among most of the shrinking implementations. Furthermore, this paper reviews the improvements to BA, which are improvements in the parameter tuning, population initialization, local search and global search. It is hoped that this paper will provide researchers who are working on improving the BA with valuable references and guidance.

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Acknowledgments

The authors would like to thank the Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, for providing facilities and financial support under Fundamental Research Grant Scheme No. AP-2102-019 entitled “Automated Medical Imaging Diagnostic Based on Four Critical Diseases: Brain, Breast, Prostate and Lung Cancer”.

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  1. Pattern Recognition Research Group, Center of Artificial Intelligence Technology, Faculty of Information Systems and Technology, Universiti Kebangsaan Malaysia, 43650, Bandar Baru Bangi, Malaysia

    Wasim Abdulqawi Hussein, Shahnorbanun Sahran & Siti Norul Huda Sheikh Abdullah

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  1. Wasim Abdulqawi Hussein
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Correspondence to Wasim Abdulqawi Hussein.

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Hussein, W.A., Sahran, S. & Sheikh Abdullah, S.N.H. The variants of the Bees Algorithm (BA): a survey. Artif Intell Rev 47, 67–121 (2017). https://doi.org/10.1007/s10462-016-9476-8

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